Remote Image ML Generalist

About the project

I run several AI initiatives that revolve around computer-vision pipelines, and I need an adaptable hand to keep our image data in perfect shape before it ever touches a model. Your main focus will be classic machine-learning groundwork: pulling raw image assets from cloud storage, auditing their quality, handling augmentations, labeling inconsistencies, and packaging everything into tidy, well-documented datasets that flow straight into our training scripts. Most tasks live in the data-preprocessing and cleaning stage, so you should be comfortable writing reproducible code for resizing, normalization, class-balancing, and automated sanity checks. We currently use Python with Pandas, NumPy, OpenCV, and sometimes Albumentations; if you have a favorite toolkit that speeds things up, I am open to it as long as it’s clearly explained and container-ready. Once a batch is processed, you’ll push it to our Git-based repo and drop a short markdown report that lists what changed, any edge cases you spotted, and the commands needed to reproduce the run. Clean commits, readable notebooks or scripts, and strict version control are non-negotiable; they keep the downstream modeling and monitoring steps painless. If this mix of autonomous, image-centric ML work suits you, let me know your typical turnaround time for a ten-thousand-image dataset and highlight a past project where your preprocessing directly improved model performance.

Skills required